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The Plant Genome : Just Published

 

Accepted, edited articles are published here after author proofing to provide rapid publication and better access to the newest research. Articles are compiled into issues at dl.sciencesocieties.org/publications/tpg, which includes the complete archive.

Citation | Articles posted here are considered published and may be cited by the doi.

Joseph, B., J.A. Schlueter, J.Du, M.A. Graham, J. Ma, and R.C. Shoemaker. 2009. Retrotransposons within Syntenic Regions between Soybean and Medicago truncatula and Their Contribution to Local Genome Evolution. Plant Genome doi:10.3835/plantgenome2009.01.0001

Current issue: Plant Genome 10(1)



  • ORIGINAL RESEARCH

    • Kathy Esvelt Klos, Belayneh A. Yimer, Ebrahiem M. Babiker, Aaron D. Beattie, J. Michael Bonman, Martin L. Carson, James Chong, Stephen A. Harrison, Amir M.H. Ibrahim, Frederic L. Kolb, Curt A. McCartney, Michael McMullen, Jennifer Mitchell Fetch, Mohsen Mohammadi, J. Paul Murphy and Nicholas A. Tinker
      Genome-Wide Association Mapping of Crown Rust Resistance in Oat Elite Germplasm

      Oat crown rust, caused by Puccinia coronata f. sp. avenae, is a major constraint to oat (Avena sativa L.) production in many parts of the world. In this first comprehensive multienvironment genome-wide association map of oat crown rust, we used 2972 single-nucleotide polymorphisms (SNPs) genotyped on 631 oat lines for association mapping of quantitative trait loci (QTL). (continued)

      Core Ideas:
      • Multienvironment genome-wide association study of reaction to crown rust in elite oat
      • Oat response to inoculation with 10 well-characterized Puccinia coronata isolates evaluated
      • Adult plant response to crown rust assessed in 10 location–years
      • Patterns of association compared against genotypes of differential gene stocks
      • QTL placed in the context of current literature

      doi:10.3835/plantgenome2016.10.0107
      Published: April 27, 2017



    • Qijian Song, Long Yan, Charles Quigley, Brandon D. Jordan, Edward Fickus, Steve Schroeder, Bao-Hua Song, Yong-Qiang Charles An, David Hyten, Randall Nelson, Katy Rainey, William D Beavis, Jim Specht, Brian Diers and Perry Cregan
      Genetic Characterization of the Soybean Nested Association Mapping Population

      A set of nested association mapping (NAM) families was developed by crossing 40 diverse soybean [Glycine max (L.) Merr.] genotypes to the common cultivar. The 41 parents were deeply sequenced for SNP discovery. Based on the polymorphism of the single-nucleotide polymorphisms (SNPs) and other selection criteria, a set of SNPs was selected to be included in the SoyNAM6K BeadChip for genotyping the parents and 5600 RILs from the 40 families. Analysis of the SNP profiles of the RILs showed a low average recombination rate. (continued)

      Core Ideas:
      • 40 NAM families were developed and 5600 RILs in the families were characterized.
      • The linkage maps for each family and a composite linkage map were constructed.
      • More than a half million high-confidence SNPs were identified and annotated.
      • Segregation distortion in most families favored alleles from the female parent.
      • The REs in the soybean genome is low.

      doi:10.3835/plantgenome2016.10.0109
      Published: April 27, 2017



    • Philomin Juliana, Ravi P. Singh, Pawan K. Singh, Jose Crossa, Jessica E. Rutkoski, Jesse A. Poland, Gary C. Bergstrom and Mark E. Sorrells
      Comparison of Models and Whole-Genome Profiling Approaches for Genomic-Enabled Prediction of Septoria Tritici Blotch, Stagonospora Nodorum Blotch, and Tan Spot Resistance in Wheat

      The leaf spotting diseases in wheat that include Septoria tritici blotch (STB) caused by Zymoseptoria tritici, Stagonospora nodorum blotch (SNB) caused by Parastagonospora nodorum, and tan spot (TS) caused by Pyrenophora tritici-repentis pose challenges to breeding programs in selecting for resistance. A promising approach that could enable selection prior to phenotyping is genomic selection that uses genome-wide markers to estimate breeding values (BVs) for quantitative traits. To evaluate this approach for seedling and/or adult plant resistance (APR) to STB, SNB, and TS, we compared the predictive ability of least-squares (LS) approach with genomic-enabled prediction models including genomic best linear unbiased predictor (GBLUP), Bayesian ridge regression (BRR), Bayes A (BA), Bayes B (BB), Bayes Cπ (BC), Bayesian least absolute shrinkage and selection operator (BL), and reproducing kernel Hilbert spaces markers (RKHS-M), a pedigree-based model (RKHS-P) and RKHS markers and pedigree (RKHS-MP). We observed that LS gave the lowest prediction accuracies and RKHS-MP, the highest. (continued)


      doi:10.3835/plantgenome2016.08.0082
      Published: April 6, 2017



    • Junping Chen, Ratan Chopra, Chad Hayes, Geoffrey Morris, Sandeep Marla, John Burke, Zhanguo Xin and Gloria Burow
      Genome-Wide Association Study of Developing Leaves’ Heat Tolerance during Vegetative Growth Stages in a Sorghum Association Panel

      Heat stress reduces grain yield and quality worldwide. Enhancing heat tolerance of crops at all developmental stages is one of the essential strategies required for sustaining agricultural production especially as frequency of temperature extremes escalates in response to climate change. Although heat tolerance mechanisms have been studied extensively in model plant species, little is known about the genetic control underlying heat stress responses of crop plants at the vegetative stage under field conditions. To dissect the genetic basis of heat tolerance in sorghum [Sorghum bicolor (L.) Moench], we performed a genome-wide association study (GWAS) for traits responsive to heat stress at the vegetative stage in an association panel. (continued)

      Core Ideas:
      • Sorghum could serve as a vital resource of heat tolerance DNA markers.
      • Natural variation of leaf traits provides understanding of heat tolerance in sorghum.
      • GWAS reveals 14 SNPs with two heat stress responsive traits in sorghum leaves.

      doi:10.3835/plantgenome2016.09.0091
      Published: March 27, 2017



    • Jose R. Lopez, John E. Erickson, Patricio Munoz, Ana Saballos, Terry J. Felderhoff and Wilfred Vermerris
      QTLs Associated with Crown Root Angle, Stomatal Conductance, and Maturity in Sorghum

      Three factors that directly affect the water inputs in cropping systems are root architecture, length of the growing season, and stomatal conductance to water vapor (gs). Deeper-rooted cultivars will perform better under water-limited conditions because they can access water stored deeper in the soil profile. Reduced gs limits transpiration rate (E) and thus throughout the vegetative phase conserves water that may be used during grain filling in water-limited environments. Additionally, growing early-maturing varieties in regions that rely on soil-stored water is a key water management strategy. (continued)

      Core Ideas:
      • QTLs for crown root angle, stomatal conductance, and maturity were identified in two field studies through the construction of a high-density bin map.
      • The QTL for stomatal conductance was associated with reduced leaf transpiration but not reduced net assimilation rate.
      • Candidate genes are proposed based on the physical location of the QTLs and the function of known genes in those locations.

      doi:10.3835/plantgenome2016.04.0038
      Published: March 27, 2017



    • Paolo Annicchiarico, Nelson Nazzicari, Luciano Pecetti, Massimo Romani, Barbara Ferrari, Yanling Wei and E. Charles Brummer
      GBS-Based Genomic Selection for Pea Grain Yield under Severe Terminal Drought

      Terminal drought is the main stress that limits pea (Pisum sativum L.) grain yield in Mediterranean-climate regions. This study provides an unprecedented assessment of the predictive ability of genomic selection (GS) for grain yield under severe terminal drought using genotyping-by-sequencing (GBS) data. Additional aims were to assess the GS predictive ability for different GBS data quality filters and GS models, comparing intrapopulation with interpopulation GS predictive ability and to perform genome-wide association (GWAS) studies. The yield and onset of flowering of 315 lines from three recombinant inbred line (RIL) populations issued by connected crosses between three elite cultivars were assessed under a field rainout shelter. (continued)

      Core Ideas:
      • GBS-based genomic predictions of pea grain yield and phenology are accurate and cost-efficient.
      • Genomic areas related to high yield and early flowering colocate under severe terminal drought.
      • Cross-population genomic predictions have quite variable predictive ability.

      doi:10.3835/plantgenome2016.07.0072
      Published: March 20, 2017



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